Post-Training at the Edge of Detectability: A Game-Theoretic Approach to Fine-Tuning.

arXiv:2607.26358v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) fine-tuning is widely used in language model training to improve performance on a target task while limiting drift from a reference policy. A standard way to balance this tra